Search results for "Cross-sectional data"

showing 3 items of 3 documents

Regression imputation for Space-Time datasets with missing values

2009

Data consisting in repeated observations on a series of fixed units are very common in different context like biological, environmental and social sciences, and different terminology is often used to indicate this kind of data: panel data, longitudinal data, time series-cross section data (TSCS), spatio-temporal data. Missing information are inevitable in longitudinal studies, and can produce biased estimates and loss of powers. The aim of this paper is to propose a new regression (single) imputation method that, considering the particular structure and characteristics of the data set, creates a “complete” data set that can be analyzed by any researcher on different occasions and using diff…

Cross-sectional dataSpace timeMissing datacomputer.software_genreRegressionTerminologyGeographyStatisticsSpace-time data imputationPerformance indicatorImputation (statistics)Data miningSettore SECS-S/01 - StatisticacomputerPanel data
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A complete system of Engel curves in the Spanish economy

2003

The main goal of this article is the estimation of the consumption–income relationship along with socio–economic factors using cross section data from the Spanish Household Expenditure Survey 1991. The data has been grouped according to exogenous criteria to avoid the problem of null expenditure. First, a non–linear system of equation is estimated, from which the linear form that best fits the used data is tested. Finally, income elasticities are calculated considering three alternative formulations depending on how an initial income increment is distributed among consumers. Income elasticities are shown for the whole income distribution

MicroeconomicsEstimationEconomics and EconometricsCross-sectional databusiness.industryIncome distributionEngel's lawNull (mathematics)Engel curveEconometricsEconomicsDistribution (economics)businessApplied Economics
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Time Trends in the Joint Distributions of Income and Age

2001

We propose a method of analyzing time changes of joint income-age densities. Change is decomposed into time invariant components which act on the densities as deformations with time varying strength. The functional form of these components is estimated non parametrically from cross sectional data. The method is applied to analyze British household data on income and age for the years 1968–95. It is learned that for the young and middle aged there is a trend towards increasing inequality, while during the early eighties there seems to occur a reversal in the evolution of the income distribution for the old.

Time changesFunctional principal component analysisCross-sectional dataInequalityIncome distributionJoint probability distributionTime trendsmedia_common.quotation_subjectEconometricsJoint (geology)Mathematicsmedia_common
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